





import sys

UpperCAmelCase_           =	(
    "73167176531330624919225119674426574742355349194934"
    "96983520312774506326239578318016984801869478851843"
    "85861560789112949495459501737958331952853208805511"
    "12540698747158523863050715693290963295227443043557"
    "66896648950445244523161731856403098711121722383113"
    "62229893423380308135336276614282806444486645238749"
    "30358907296290491560440772390713810515859307960866"
    "70172427121883998797908792274921901699720888093776"
    "65727333001053367881220235421809751254540594752243"
    "52584907711670556013604839586446706324415722155397"
    "53697817977846174064955149290862569321978468622482"
    "83972241375657056057490261407972968652414535100474"
    "82166370484403199890008895243450658541227588666881"
    "16427171479924442928230863465674813919123162824586"
    "17866458359124566529476545682848912883142607690042"
    "24219022671055626321111109370544217506941658960408"
    "07198403850962455444362981230987879927244284909188"
    "84580156166097919133875499200524063689912560717606"
    "05886116467109405077541002256983155200055935729725"
    "71636269561882670428252483600823257530420752963450"
)
def      A__       (    SCREAMING_SNAKE_CASE_   :      str = N						)  ->  int:






   """simple docstring"""







   _UpperCAmelCase           =   -sys.maxsize - 1
   for i in range(len(SCREAMING_SNAKE_CASE_						) - 12						):
      _UpperCAmelCase           =   1
      for j in range(13						):
         product *= int(n[i + j]						)
      if product > largest_product:
         _UpperCAmelCase           =   product
   return largest_product


if __name__ == "__main__":
   print(f'''{solution() = }''')




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


a      :  Dict			     =			{
    'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertConfig'],
    'tokenization_lxmert': ['LxmertTokenizer'],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a      :  Any			     =			['LxmertTokenizerFast']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a      :  str			     =			[
	    'LxmertEncoder',
	    'LxmertForPreTraining',
	    'LxmertForQuestionAnswering',
	    'LxmertModel',
	    'LxmertPreTrainedModel',
	    'LxmertVisualFeatureEncoder',
	    'LxmertXLayer',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a      :  str			     =			[
	    'TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFLxmertForPreTraining',
	    'TFLxmertMainLayer',
	    'TFLxmertModel',
	    'TFLxmertPreTrainedModel',
	    'TFLxmertVisualFeatureEncoder',
	]


if TYPE_CHECKING:
	from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
	from .tokenization_lxmert import LxmertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_lxmert_fast import LxmertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_lxmert import (
		    LxmertEncoder,
		    LxmertForPreTraining,
		    LxmertForQuestionAnswering,
		    LxmertModel,
		    LxmertPreTrainedModel,
		    LxmertVisualFeatureEncoder,
		    LxmertXLayer,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_lxmert import (
		    TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFLxmertForPreTraining,
		    TFLxmertMainLayer,
		    TFLxmertModel,
		    TFLxmertPreTrainedModel,
		    TFLxmertVisualFeatureEncoder,
		)

else:
	import sys

	a      :  str			     =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






